Abstract: The present disclosure is directed to data classification. An exemplary computer-enabled method for classifying image data comprises: receiving an input image, wherein the input image is of a second data domain; providing the input image to a preprocessing algorithm to obtain a transformed image, wherein the preprocessing algorithm is trained to transform data of the second data domain to data of a first data domain; providing the transformed image to a trained algorithm to analyze the transformed image, wherein the trained algorithm is trained based on training data of the first data domain.

Abstract: The present disclosure is directed to data classification. An exemplary computer-enabled method for classifying image data comprises: receiving an input image, wherein the input image is of a second data domain; providing the input image to a preprocessing algorithm to obtain a transformed image, wherein the preprocessing algorithm is trained to transform data of the second data domain to data of a first data domain; providing the transformed image to a trained algorithm to analyze the transformed image, wherein the trained algorithm is trained based on training data of the first data domain.

Abstract: The present disclosure is directed to data classification. An exemplary computer-enabled method for classifying image data comprises: receiving an input image patch, wherein the input image patch is of a second data domain; providing the input image patch to a preprocessing algorithm to obtain a preprocessed image patch, wherein the preprocessing algorithm is trained to transform data of the second data domain to data of a first data domain; providing the preprocessed image patch to a pre-trained classification algorithm, wherein the pre-trained classification algorithm is trained based on training data of the first data domain; obtaining one or more classification outputs from the pre-trained classification algorithm based on the preprocessed image patch.

Abstract: The present disclosure is directed to data classification. An exemplary computer-enabled method for classifying image data comprises: receiving an input image patch, wherein the input image patch is of a second data domain; providing the input image patch to a preprocessing algorithm to obtain a preprocessed image patch, wherein the preprocessing algorithm is trained to transform data of the second data domain to data of a first data domain; providing the preprocessed image patch to a pre-trained classification algorithm, wherein the pre-trained classification algorithm is trained based on training data of the first data domain; obtaining one or more classification outputs from the pre-trained classification algorithm based on the preprocessed image patch.

Abstract: A computer implemented method, a computer program product, and data processing system clone virtual machines in a virtual desktop environment. A request to clone a new virtual machine is intercepted, wherein the request was initially sent to a virtual management server. Responsive to intercepting the request, the new virtual machine is cloned from a snapshot of a master virtual machine. A delta file is created for the new virtual machine, wherein the delta file includes a base disk reference and a copied delta file. The new virtual machine is configured to read a base disk image from a snapshot of the master virtual machine. The new virtual machine is configured to write data to the copied delta file in the delta file.

Abstract: A computer implemented method, a computer program product, and data processing system clone virtual machines in a virtual desktop environment. A request to clone a new virtual machine is intercepted, wherein the request was initially sent to a virtual management server. Responsive to intercepting the request, the new virtual machine is cloned from a snapshot of a master virtual machine. A delta file is created for the new virtual machine, wherein the delta file includes a base disk reference and a copied delta file. The new virtual machine is configured to read a base disk image from a snapshot of the master virtual machine. The new virtual machine is configured to write data to the copied delta file in the delta file.

Abstract: Memory is managed by controlling the expansion of memory contents, especially in those computing environments in which the memory contents are compressed. Control is provided by imposing some restrictions to memory references outside a specified subset of the memory contents, and by controlling the transfer of items into the subset. In one example, the transfer of items into the subset is based on a function of parameters, including an estimate of the amount of free space in the memory.

Abstract: A system and method for extracting data from a protected region of memory loads at least a first part of extraction code into physical memory and, thereafter, activates a memory mapping facility that maps a real memory onto the physical memory and prevents programs from accessing a protected memory region of the physical memory. At least a second part of the extraction code is then loaded into the virtual memory utilizing the memory mapping facility. The extraction code is then executed to deactivate the memory mapping facility and to copy data from the protected memory region to a second physical memory region, such that reactivating the memory mapping facility will cause a real memory region to be mapped onto the second physical memory region.

Abstract: An aquarium filter system having a rotatably mounted filter body. The filter body is structured such that when mounted with a portion of the filter body submerged in moving water, rotational movement is imparted to the filter body by the moving water. As a result of the rotational movement, at least a portion of the filter body is alternately exposed to the water and the atmosphere. This fosters the growth of aerobic bacteria on the surface of the filter body. The aerobic bacteria reduces the level of toxins within the aquarium water.

Abstract: An aquarium filter system having a rotatably mounted filter body. The filter body is structured such that when mounted with a portion of the filter body submerged in moving water, rotational movement is imparted to the filter body by the moving water. As a result of the rotational movement, at least a portion of the filter body is alternately exposed to the water and the atmosphere. This fosters the growth of aerobic bacteria on the surface of the filter body. The aerobic bacteria reduces the level of toxins within the aquarium water.